1. Field of the Invention
The present invention relates to a data management system and method.
2. Discussion of Related Art
Recently, big data has been actively researched and used. Nowadays, the big data era has been begun with many innovations coming simultaneously from numerous sources, such as theorists, system builders, scientists or application designers.
With the increasing amounts of data as well as diverse demands on data, more and more data centers have been built geographically in many places for various data services. Each separated data center has different goals, infrastructures and software specifications. Thus, it is difficult to manage data of each separated data center in an integrated manner.
During operation of many data services, it is important to provide operation analysis for service optimization such as system failure diagnosis, error detection or access prediction. However, a system extended to analyze service tasks between separated data centers has not yet been developed, thereby reducing a possibility to apply the operation analysis for service optimization to platforms.
FIG. 1 is a block diagram of a data management system according to the related art.
For optimized operations of services, in the data management system according to the related art, task analysis clusters 20-1 to 20-4 are respectively used in data centers 10-1 to 10-4 installed separately in regions A-1 to A-4 as illustrated in FIG. 1.
However, the related art is limited in being applied to the field of big-data platform due to the following reasons.
First, there is no external cooperation among the task analysis clusters 20-1 to 20-4. That is, it is impossible to analyze a task performed through cooperation among the data centers 10-1 to 10-4.
Second, the data centers 10-1 to 10-4 have different demands for a task analysis and thus it is difficult to balance resources and maintain an optimized state. For example, one cluster has insufficient resources but another cluster does not receive a task analysis request and thus does not use resources. Thus, resources of the data centers 10-1 to 10-4 may be maintained in imbalanced states.
Lastly, the number of devices included in each of the task analysis clusters 20-1 to 20-4 is limited. Thus, according to the related art, a large amount of data cannot be processed, thereby causing fatal problems in the field of big-data platform.
In this connection, Korean laid-open patent publication No. 10-2015-0091901, entitled “Dispersed Parallel Big Data Processing System”, discloses a big data processing system capable of processing big data in parallel in a dispersed manner.